Autonomous tracking and sampling of the deep chlorophyll maximum layer in an open-ocean eddy by a long-range autonomous underwater vehicle

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Zhang, Y., Kieft, B., Hobson, B. W., Ryan, J. P., Barone, B., Preston, C. M., Roman, B., Raanan, B., Marin,Roman,,III, O'Reilly, T. C., Rueda, C. A., Pargett, D., Yamahara, K. M., Poulos, S., Romano, A., Foreman, G., Ramm, H., Wilson, S. T., DeLong, E. F., Karl, D. M., Birch, J. M., Bellingham, J. G., & Scholin, C. A. Autonomous tracking and sampling of the deep chlorophyll maximum layer in an open-ocean eddy by a long-range autonomous underwater vehicle. IEEE Journal of Oceanic Engineering, 45(4), (2020): 1308-1321, doi:10.1109/JOE.2019.2920217.Phytoplankton communities residing in the open ocean, the largest habitat on Earth, play a key role in global primary production. Through their influence on nutrient supply to the euphotic zone, open-ocean eddies impact the magnitude of primary production and its spatial and temporal distributions. It is important to gain a deeper understanding of the microbial ecology of marine ecosystems under the influence of eddy physics with the aid of advanced technologies. In March and April 2018, we deployed autonomous underwater and surface vehicles in a cyclonic eddy in the North Pacific Subtropical Gyre to investigate the variability of the microbial community in the deep chlorophyll maximum (DCM) layer. One long-range autonomous underwater vehicle (LRAUV) carrying a third-generation Environmental Sample Processor (3G-ESP) autonomously tracked and sampled the DCM layer for four days without surfacing. The sampling LRAUV's vertical position in the DCM layer was maintained by locking onto the isotherm corresponding to the chlorophyll peak. The vehicle ran on tight circles while drifting with the eddy current. This mode of operation enabled a quasi-Lagrangian time series focused on sampling the temporal variation of the DCM population. A companion LRAUV surveyed a cylindrical volume around the sampling LRAUV to monitor spatial and temporal variation in contextual water column properties. The simultaneous sampling and mapping enabled observation of DCM microbial community in its natural frame of reference.10.13039/501100008982 - National Science Foundation 10.13039/100000936 - Gordon and Betty Moore Foundation 10.13039/100000008 - David and Lucile Packard Foundation 10.13039/100016377 - Schmidt Ocean Institute 10.13039/100000893 - Simons Foundatio

Functionality and feedback: a realist synthesis of the collation, interpretation and utilisation of patient-reported outcome measures data to improve patient care

Background: The feedback of patient-reported outcome measures (PROMs) data is intended to support the care of individual patients and to act as a quality improvement (QI) strategy. Objectives: To (1) identify the ideas and assumptions underlying how individual and aggregated PROMs data are intended to improve patient care, and (2) review the evidence to examine the circumstances in which and processes through which PROMs feedback improves patient care. Design: Two separate but related realist syntheses: (1) feedback of aggregate PROMs and performance data to improve patient care, and (2) feedback of individual PROMs data to improve patient care. Interventions: Aggregate – feedback and public reporting of PROMs, patient experience data and performance data to hospital providers and primary care organisations. Individual – feedback of PROMs in oncology, palliative care and the care of people with mental health problems in primary and secondary care settings. Main outcome measures: Aggregate – providers’ responses, attitudes and experiences of using PROMs and performance data to improve patient care. Individual – providers’ and patients’ experiences of using PROMs data to raise issues with clinicians, change clinicians’ communication practices, change patient management and improve patient well-being. Data sources: Searches of electronic databases and forwards and backwards citation tracking. Review methods: Realist synthesis to identify, test and refine programme theories about when, how and why PROMs feedback leads to improvements in patient care. Results: Providers were more likely to take steps to improve patient care in response to the feedback and public reporting of aggregate PROMs and performance data if they perceived that these data were credible, were aimed at improving patient care, and were timely and provided a clear indication of the source of the problem. However, implementing substantial and sustainable improvement to patient care required system-wide approaches. In the care of individual patients, PROMs function more as a tool to support patients in raising issues with clinicians than they do in substantially changing clinicians’ communication practices with patients. Patients valued both standardised and individualised PROMs as a tool to raise issues, but thought is required as to which patients may benefit and which may not. In settings such as palliative care and psychotherapy, clinicians viewed individualised PROMs as useful to build rapport and support the therapeutic process. PROMs feedback did not substantially shift clinicians’ communication practices or focus discussion on psychosocial issues; this required a shift in clinicians’ perceptions of their remit. Strengths and limitations: There was a paucity of research examining the feedback of aggregate PROMs data to providers, and we drew on evidence from interventions with similar programme theories (other forms of performance data) to test our theories. Conclusions: PROMs data act as ‘tin openers’ rather than ‘dials’. Providers need more support and guidance on how to collect their own internal data, how to rule out alternative explanations for their outlier status and how to explore the possible causes of their outlier status. There is also tension between PROMs as a QI strategy versus their use in the care of individual patients; PROMs that clinicians find useful in assessing patients, such as individualised measures, are not useful as indicators of service quality. Future work: Future research should (1) explore how differently performing providers have responded to aggregate PROMs feedback, and how organisations have collected PROMs data both for individual patient care and to improve service quality; and (2) explore whether or not and how incorporating PROMs into patients’ electronic records allows multiple different clinicians to receive PROMs feedback, discuss it with patients and act on the data to improve patient care